Estimated numbers of Covid19 antibodies based in random samples in Santa Clara County reveals approximately 75 times more people had COVID-19 than actual government reporting numbers. What this means; the numbers we have been using for symptom reporting and mortality may be all wrong. – Anthony
COVID-19 Antibody Seroprevalence in Santa Clara County, California
Eran Bendavid, Bianca Mulaney, Neeraj Sood, Soleil Shah, Emilia Ling, Rebecca Bromley-Dulfano, Cara Lai, Zoe Weissberg, Rodrigo Saavedra, James Tedrow, Dona Tversky, Andrew Bogan, Thomas Kupiec, Daniel Eichner, Ribhav Gupta, John Ioannidis, Jay Bhattacharya
doi: https://doi.org/10.1101/2020.04.14.20062463
Abstract
Background Addressing COVID-19 is a pressing health and social concern. To date, many epidemic projections and policies addressing COVID-19 have been designed without seroprevalence data to inform epidemic parameters. We measured the seroprevalence of antibodies to SARS-CoV-2 in Santa Clara County. Methods On 4/3-4/4, 2020, we tested county residents for antibodies to SARS-CoV-2 using a lateral flow immunoassay. Participants were recruited using Facebook ads targeting a representative sample of the county by demographic and geographic characteristics. We report the prevalence of antibodies to SARS-CoV-2 in a sample of 3,330 people, adjusting for zip code, sex, and race/ethnicity. We also adjust for test performance characteristics using 3 different estimates: (i) the test manufacturer’s data, (ii) a sample of 37 positive and 30 negative controls tested at Stanford, and (iii) a combination of both. Results The unadjusted prevalence of antibodies to SARS-CoV-2 in Santa Clara County was 1.5% (exact binomial 95CI 1.11-1.97%), and the population-weighted prevalence was 2.81% (95CI 2.24-3.37%). Under the three scenarios for test performance characteristics, the population prevalence of COVID-19 in Santa Clara ranged from 2.49% (95CI 1.80-3.17%) to 4.16% (2.58-5.70%). These prevalence estimates represent a range between 48,000 and 81,000 people infected in Santa Clara County by early April, 50-85-fold more than the number of confirmed cases.
Conclusions
The population prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that the infection is much more widespread than indicated by the number of confirmed cases. Population prevalence estimates can now be used to calibrate epidemic and mortality projections.
yet another study indicating the lower lethality of the virus.
But lethal enough. More dead from this in a month and a half than died all of last year in car accidents.
Well, you are wrong. 38,900 deaths in 2019 in car accidents. 35,955 to Covid-19 thus far.
And that is of course an apples to oranges comparison.
80,000 died of flu in 2018. We are supposedly past the peak for this virus, so 72,000 may die, probably closer to 55,000.
I really do hate the comparison to the flu. Reason, new disease, ADDS to existing chance of dying. So NOW during the year, we can have 80k die of the flu AND 80k die from Corona as well.
A new way to die is just not fun.
That’s not the way it works. Once low-hanging fruit gets picked off there’s not any left for the next illness.
Well, no. Covid19 competes with the flu virus. If you’re eighty years old and have asthma, there are various competing pathogens eager to finish you off. So it is not additive.
Timo, EVERONE dies. Not a single life was saved by destroying the economy. All we did was prevent deaths. In reality, we haven’t and won’t beat the virus (not a disease). All we have done is delay its spread. Eventually you will get it. There might be a vaccine next year but we have a lot of viruses that have been around for generations that don’t have vaccines.
Actually not a correct way to look at it. In my state we were in the midst of an above average flu season with above average deaths from Oct 1 to March 31. The number of flu cases and deaths cratered after than point. Well below 5 year averages. Deaths from Covid–19 took over for the flu related deaths.
Jeremiah … “All we have done is delay its spread.”
According to the above article, we haven’t even done that very effectively. There are about 25,000 confirmed cases in California. The articles says it could really be 80 times that much =2,000,000 = 5% of the population.
“So NOW during the year, we can have 80k die of the flu AND 80k die from Corona as well”
Not only is it not additive as other have pointed out, flu season got in first and it was not a big flu year. If it had been maybe we would not be freaking out about covid because the weak would already have been kulled.
I wouldn’t worry too much.
The median age of the deceased in most countries (including Italy) is over 80 years and only about 1% of the deceased had no serious previous illnesses. The age and risk profile of deaths thus essentially corresponds to normal mortality.
But flu deaths are now counted as Covid, if they just have covid in their system at death…
Seen, a number of times, that wash-your-hands, don’t-touch-your-face, six-feet-of-distance protocols would likely result in fewer flu cases. The old are dying of one, instead of the other, so in that respect it’s a wash.
As a campaign strategy, continued lockdown is a despicable one.
Well NO, in reality less than HALF that so FAR but at least with the FLU we have a modicum of IMMUNITY with something like a best GUESS at a yearly vaccine that MIGHT prevent that particular STRAIN of inFLUENZA for that YEAR.
But with NO vaccine for “Corona,” AND with less deaths than Influenza (all strains) this MUST mean SOMETHING, mustn’t it?
Not so. It only adds if it is a new way of dying. Flying added to your risk, but a new respiratory disease literally competes with others to infect you.
If that is the case, show us the numbers that prove it is additive.
My hunch is the total deaths this year will not vary much from previous years. The only difference will be how those deaths are classified.
Apart from 2017/18 vulnerable demographic is vaccinated against Flu.
Well now, you heard what happened to the dinosaur population when they were subjected to the Megareptilian virus pandemic. 😊
Don’t forget that the USA is counting anyone who died with the virus as dying because of the virus. So if you have a heart attack, you died of Covid19. We also have rumors that places like NY are inflating numbers. Obviously when we pass a spending bill that gives money to states for every Covid death, you’re going to have at least a minimal amount of inflation.
And if the vast majority are asymptomatic then how many actually had their deaths affect by the virus?
Wow, what a motivation to test for Covid: The State gets money for every case. Almost impossible to avoid some over-reporting.
I heard this on the news and nowhere else so is it true? I don’t know. Anyway it was said that NY want back and looked at non COVID related deaths and made a determination if they would of lived if the hospitals had not been slammed with COVID patients. If they determine the person should of lived they are counting it as a COVID related death and adjusting death tolls accordingly. This is where the big spike in additional deaths came from.
Wow, I said this must be the case as soon as I heard about NY 3,700 case jump but had not got as far as researching it.
50% inflation is more than “minimum”, it’s simple theft.
@Darrin:
” could of lived … should of lived” . For goodness sake, should’ve may sound like “should of”but it’s short for should have.
astiberii, that “80,000” estimate for the 2017-2018 flu death toll was later revised downward to 61,000. Even so, it was not typical. It was the worst flu season of the last nine.
Over the last nine flu seasons, the CDC estimate of the average U.S. flu death toll was 37,462 flu deaths per year, spread over flu seasons which lasted about six months, and caused an average of about 28.65 million flu cases per flu season. The average fatality rate from seasonal flu in the U.S. was thus about 0.13%.
One of the main reasons the average number of flu infections was so low (under 30 million) is that about half of Americans get the flu vaccine jab each year.
The latest U.S. COVID-19 figures are 40,524 dead, and 763,579 known cases, of which 85.4% are still unresolved.
More than 40,000 of those deaths were within the last four weeks.
The naively-calculated U.S. fatality rate from COVID-19 now stands at 5.3%.
There are two factors which make the naively-calculated fatality rate different from the true fatality rate:
1. 85.4% of the known cases are still unresolved, and thousands of them will die. That causes an underestimate of the fatality rate.
2. The United States, to our discredit, currently does not diagnose most asymptomatic cases. So we probably have had between 1.1 and 4.6 undiagnosed COVID-19 cases for every known case (best estimate 2.85). That underestimate of the true number of cases causes an overestimate of the fatality rate.
Through intensive testing and contact tracing, the South Koreans have identified nearly all of their COVID-19 cases, including the asymptomatic cases. From their data (the best & most complete data we have), we can calculate that COVID-19 has a fatality rate of 2.5% ±0.4% in the best of circumstances: i.e., with early detection and highly competent medical care.
It is not plausible that the U.S. fatality rate could be lower than that. So that’s a lower bound on the true U.S. COVID-19 fatality rate. The only way the true fatality rate could fall substantially below that is if an effective treatment is found & deployed.
Thanks to draconian lockdowns, and despite the inexcusable refusals of big city mayors and governors to shut down disease-spreading mass transit systems, the U.S. statistics have plateaued, but at horrific levels. We are not “past the peak” for this disease. The U.S. has been averaging around 30,000 new cases per day for the last 18 days, and we’ve been averaging around 2,000 deaths per day for the last 12 days.
Go to this page and scroll down to see those graphs:
https://www.worldometers.info/coronavirus/country/us/
There’s a lot of misinformation circulating from fake experts, claiming that the death toll and infectiousness of this disease are similar to the flu. It is untrue, do not believe it.
One recent “study” hypothesizes (based on remarkably scant evidence!) that there’ve been 28 million undetected COVID-19 cases in the United States, which were so mild that the infected people didn’t know that had the disease. That would be 8.5% of the U.S. population. It is complete poppycock.
If that many Americans had really been infected, then nearly everyone would have been exposed by now. There would be no remaining large populations free of the disease.
If that were the case, then the sudden, explosive outbreaks seen when populations like nursing homes, ships & prisons are infected could not happen. They only happen because those large populations, of hundreds or thousands of individuals, start out with NO infections at all.
If 8.5% of the U.S. population had really been infected then there’d be no remaining large populations with no infections at all.
It would also mean that for every symptomatic patient, about 70 others were either asymptomatic or had symptoms so mild that they weree overlooked. That is obviously preposterous, because we know from various contained populations (prisons, ships, nursing homes, Diamond Princess) that only about half of those infected are asymptomatic.
If we implement the commonsense measures which enabled South Korea to beat the virus, then we can bring both the daily new case number and the daily death toll rapidly down, and we can then lift the lock-downs and reopen the closed businesses. If we don’t implement those measures, then it will be a long, brutal summer, with widespread human and economic devastation.
Here are two articles about how South Korea succeeded, while most other nations, including the United States, are failing spectacularly:
1. https://wattsupwiththat.com/2020/04/08/boris-johnson-in-intensive-care/ (starting around the 15th paragraph)
2. https://www.businessinsider.com/how-south-korea-controlled-its-coronavirus-outbreak-2020-4
Dave Burton: “If we implement the commonsense measures which enabled South Korea to beat the virus, then we can bring both the daily new case number and the daily death toll rapidly down, and we can then lift the lock-downs and reopen the closed businesses. If we don’t implement those measures, then it will be a long, brutal summer, with widespread human and economic devastation.”
WR: This is the correct message, based on well calculated numbers. To be compared with a worst case scenario as we know it from 1918: see below.
The 2.5% Case Fatality Rate for South Korea is for now the lowest number possible. Without CONTROL OF THE VIRUS that number will be way higher when is chosen for a ‘Full Blown Epidemic”. Although in 1918 more countries have known very bad scenarios it is Iran that stands out as one of the hardest hit.
The 1918 Spanish Flu was devastating, at one place more than the other. One of the most severely hit countries was Iran. Three armies brought in the flu from various directions and combined with other sicknesses like malaria and anemia and in combination with the total disarray caused by the Great War a worst case scenario resulted.
The total death rate for Iran (not the ‘Case Fatality Rate!) has been estimated to be “between 8.0% and 21.7% of its total population”: dead.
Worst case scenario: by a flu, by other factors and by a total disarray. That is why we need control of the virus. It is possible to control: South Korea (and Taiwan and others) show how.
Source Iran 1918: https://hsrc.himmelfarb.gwu.edu/cgi/viewcontent.cgi?referer=https://en.wikipedia.org/&httpsredir=1&article=1384&context=smhs_psych_facpubs
The way Taiwan controls: https://www.telegraph.co.uk/global-health/science-and-disease/taiwans-vice-president-chen-chien-jen-countrys-fight-covid-19/
Note that Silverman, Hupert & Washburne did not actually count COVID-19 cases. They simply hypothesized that excess “flu-like illnesses” in places which later had COVID-19 outbreaks were actually COVID-19. It’s a very weak argument.
https://twitter.com/az_reason/status/1249942566717362181
Here’s the preprint of their paper (thus far not peer-reviewed):
https://www.medrxiv.org/content/10.1101/2020.04.01.20050542v2.full.pdf
That is not true for the US. More than 32,000 die every year from vehicle accidents.
But you are right that this pandemic is lethal enough, and people should not be encouraged
to further risk taking. There’s already enough of that to go around. Cancer kills much more than COVid would if left unchecked, over a half million a year in the US, many as a result of risk taking behaviors such as smoking, drinking and bad diet.
So, in other words, if we used a few trillions on smoking cessation, we could save half a million relatively young people. How about if we gave each smoker $1 million to not smoke. That would be a very cheap way of saving half a million lives.
But the more years you add on to a former smoker’s life, the more money spent on his other various healthcare costs during his extended lifetime. Of course such costs are mitigated if that person is a productive member of the workforce, thereby contributing in some health insurance plan.
The numbers are bogus. NYC inflated their deaths numbers by 50% simply by assuming, without any testing, that 3700 deaths were due to corona-chan
No they report
TWO DIFFERENT CATEGORIES.
the NYT is wrong
It doesn’t surprise me if the NYT is wrong on any given subject matter upon which they report. But if you’re objecting to the notion that C-19 deaths are inflated I’d like to hear your argument to that.
“It doesn’t surprise me if the NYT is wrong on any given subject matter upon which they report. But if you’re objecting to the notion that C-19 deaths are inflated I’d like to hear your argument to that.”
yes I object to Notions.
There are reasons to believe in an undercount and overcount.
Notions abound. I object to all notions.
Now, here a SPECIFIC claim is made.
New york is including “probable deaths” as real deaths.
They are not. Even steve mcintrye looking at the data can see that there are
Two COLUMNS
1. for died with a positive diagnosis
2. Died with no cause of death, but suspected covid.
Nobody combines 1 +2 except for the NYT and other misreportings
This was covered in the daily briefings in New York
So, “notions” abut over or under counting, yes I object to notions.
Arguments with data? I evaluate those.
Notions? I object
Arguments with data. I evaluate
I gotcha. If that’s all your saying then yeah, he’s wrong:
https://www1.nyc.gov/assets/doh/downloads/pdf/imm/covid-19-daily-data-summary-deaths-04172020-1.pdf
Oh and one more thing:
😛
Try the CDC reporting guidelines. A positive test has to be mentioned on the death certificate. Announced deaths are those where COVID is mentioned on the death certificate plus those where a doctor believes COVID was a cause.
But it is very close to typical flu lethality. In principle, if we think a bit outside the box, Covid could be just some benign virus spreading in the population, and people die from the soup of flu viruses that are not tested for. Just imagine that we decided to test another flu virus, let’s call it porona, and got the same results: typical flu mortality. We would then say that we have a porona epidemic. Actually, I bet if the tested for Swine flu, we would get the same results as for Corona.
What I find interesting is that we have high mortality with the flu and WE HAVE A VACCINE for it. What would it be every year without that? COVID does not yet have a vaccine, but from what I have read, it is expected to mutate only slowly so whatever immunity you get will last for more than a season.
BTW, also a good article in the WSJ about vitamin D3 deficiency contributing to the excess deaths of darker skinned individuals of all races.
I’ve read that I have that problem. all three races,and dark skin. I have to take vitamin D supplements to keep it up even in the summer. that said I have suspected that i may have had CoV-2 back at the end of November.
Had Fever, Chills ended up in the patted me on the head sent me home with Tylenol and an antibiotic. Got better in 3 days but had it total for a week.
What I glean from this paper is that it has been here a while. I live in the
High Lonesome of NE Oregon. but we have a freeway going through town.
So there is a possibility.
I’d like to take an antibody test.
A lot of people in Oregon got something, starting in November.
Douglas,
After the Chinese restaurant birthday thing about 10 people came down with something similar. My Dad, in the red zone, spent a few nights in the hospital … “not flu” they said, some sort of “sticky lung” thing. It took him a few months (including a small relapse) to get past the whole thing.
It may be very interesting to see the results of the widespread & individual antibody tests.
Vaccines for seasonal flu are mostly not effective because the seasonal flu mutates every year. The vaccine for last year is not very effective for this year, etc. Look it up. https://www.cnn.com/2020/01/14/health/flu-vaccine-match/index.html
4EDouglas & DonM, After visiting Bend, OR for a weekend in early March, I had a dry cough with a fever and fatigue. Oregon does seem to be a hot spot for something.
SR
Your assumptions are based on incomplete information.
Since there a relative lack of Wuhan virus tests vis-avis influenza tests, patients are tested for the flu first.
“Former NIH Researcher” wrote, “But it is very close to typical flu lethality.”
No, it isn’t. COVID-19 is about twenty times as lethal as typical seasonal flu.
And COVID-19 is also considerably more infectious.
And there’s currently no vaccine for COVID-19.
And COVID-19 is apparently infectious even from asymptomatic patients.
Those factors combine to make this pandemic far, far worse then any seasonal flu. It’s more like the 1918 Spanish flu pandemic, which is estimated to have killed about 2% of the entire world’s population.
Note: it wasn’t just 2% of those infected. It was 2% of everyone.
The problem is that they are often conflating the flu deaths with the non-flu deaths. The numbers jumped recently as they decided to decide Covid deaths to be based on symptoms and opinion. It’s a bogus number. The total death is still with in the normal range of a flu season.
Then, there is the problem that they are assuming they are even looking at a specific virus and not a salad of viruses. They do not check to see if other viruses are present and make no attempt to be discerning, just jump to conclusions.
Simply wrong. The COVID death are anybody who dies having tested positive. If I test position Monday, have heart attack Tuesday and die on Wednesday, COVID is on my death certificate.
So nothing like that number have actually died from the virus.
Plus, in cases of no testing, if decedent had respiratory distress due to COPD, lung cancer, emphysema, Etc., assume Covid-19 must be cause of death.
The UK’s Covid-19 today’s (Friday) update:
http://www.vukcevic.co.uk/UK-COVID-19.htm
Since there is such a big pool of positive cases, the whole pandemic could be an illusion based on anxiety. Media makes anxiety for covid rise at the same time as testing proficiency rises. People have to be sufficiently worried to want to be tested. This fear can easily rise exponentially. And since there is at least 50 times as many infected as confirmed tests, there is no shortage of test positive individuals in a cross section of worried persons. After a while the pool of worried people is exhausted, positive tests flatten and this makes the fear in the population lower. Fewer are motivated to be tested and there is an exponential decline in cases.
Those who die 14 days later belong to his artificial pool of tested people, and will follow the same curve as the positive tests plus a few tested after death.
I agree with this (Former NIH) hypothesis.
Sometimes problem descriptions have too many incorrect assumptions leading to incorrect solutions. And if, as in this hypothesis, one assumes a benign and widely distributed virus instead of a deadly one, the results might be the same. All that’s necessary to make the ‘former NIH’ hypothesis work is changing other assumptions that few are looking at. The ‘nocebo effect’, fear might be causing deaths along with seasonal flu being counted as Covid-19 could make this hypothesis the correct problem description. The cure might be to stop the media hyperbole.
In my opinion I think we are being Gaslighted. https://en.wikipedia.org/wiki/Gaslighting
The test is worthless unless it has been shown to be specific for a single virus. The gold standard test has not been applied. As there are many coronaviruses out there, the test has to also show that it can pick out the specific virus from a mixture of similar viruses. Nothing of the kind has been shown. Instead, we have a “PCR” test for RNA in general and not any specific virus. We have rapid tests that simply cannot be discerning using PCR and must be detecting more generally. So, are we testing for overall RNA levels or overall coronavirus levels and simply assuming that everything is Covid-19. That’s just stupid.
The paper referred to at top refers to an anti body test for Covid 19. Is that any more descriminating amoung the half dozen or existing human Corona viruses?
They seem to have some amazing results, population adjusted 80 x more than expected of people with covid anti bodies. There is some peer review which doesn’t like some of the false positives rate which could completely change the numbers and they promoted the free test on Facebook and may have become back door method for those wanting a zero cost test after friends tested positive
Not true. The test is specific for this virus.
Am interested to know for sure if the tests are Covid 19 specific or not – does anybody on here know – surely they must be?
Amen…. so little is known about this allegedly ‘synthetic Gain-of-function, recombinant DNA cored virus with both a HIV tale and Streptococcal tale, no wonder the “authorities’ are so concerned to maintain strict anti-spread controls in place until more is known about lethality rates and contagion recurrence potentials…
Some blood-types seem more susceptible to infection resulting in more severe symptoms and higher death-rates…
See
another very knowledgeable source says that the coronavirus is manmade.
https://www.gilmorehealth.com/chinese-coronavirus-is-a-man-made-virus-according-to-luc-montagnier-the-man-who-discovered-hiv/
If he’s right, then the “debunked” Indian scientists forced to retract their paper are exonerated.
Speaking as someone who made their living doing this stuff, I say that’s garbage and the good doctor is either going senile or his quotes are being taken out of their whole context. (I suspect the latter.) We have the sequence. Therefore we know what this virus is and where it came from. I t cold have come from the market. Given more information about their patient zero being a staff member and that the Wuhan lab was studying cornovirueses, I do think it far more likely it came out of the Wuhan lab than the wet market. Nonetheless, it is a known virus. The Chinese were collecting and growing natural viruses in that lab. There are legitimate reasons to do so. There are also nonlegitimate reasons.
There is some plausible intelligence, that indicates that they were growing natural virus strains so they could have the vaccines ready when the stuff hit the fan, and subsequently be both the savior of the world and make big bucks. It’s kind of like reverse biological warfare
Matt Ridley wrote a piece in WSJ claiming that the novel coronavirus was just found in a guano sample from 2013 which had been stored for SARS research.
Mark,
That seems to be the most logical explanation. Head over to Jo Nova’s site for a different take.
The insertion of HIV genes into the virus is a competing theory. the story is rather weak but worth a read.
They were not only collecting and studying natural corona viruses they had ENGINEERED and isolated a chemera capable of infecting human airway cell tissue.
This was published PR science, not tin foil C.T.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4797993/pdf/41591_2015_Article_BFnm3985.pdf
Well right, reds under the beds group but documents all check out.
https://www.youtube.com/watch?v=3bXWGxhd7ic
bioweapons angle is plausible but far from proven. However, it was 100% a leak of an engineered virus strain. In view of the openness, it seems unlikely THIS work was biowarfare.
Having the sequence of a virus does not mean it is the one causing this illness. Did they test it on people? I think not. There are many coronaviruses out there and everybody is considering the one sequence to be the last word. Has it been verified. I have been unable to find confirmation.
Justin, I read somewhere that the sequence of an early specimen was found to contain remnants of shuttle vectors, suggesting that it was therefore constructed in a lab. Trouble is, it’s almost impossible to discern which reports are true. Is the sequence info published credible? What’s your opinion on this?
So everyone who gets covid19 and survives is vaccinated against HIV! If as Montagnais says the coronavirus containing HIV fragments was being developed as an AIDS vaccine.
Uh no. It does not work that way. The HIV fragment had like 80+ more sequences with better matching and it bound to a common human receptor that all viruses have to fit into. No way. Dream stuff.
another very knowledgeable source says that the coronavirus is manmade.
That won’t count – he will be mocked:
“That does not make sense. These are very small elements that we find in other viruses of the same family, other coronaviruses in nature,” virologist Étienne Simon-Lorière of the Institut Pasteur in Paris, explained to AFP.
“These are pieces of the genome that actually look like lots of sequences in the genetic material of bacteria, viruses and plants,” he says.
https://asiatimes.com/2020/04/french-prof-sparks-furor-with-lab-leak-theory/
“actually look like ” we are not talking “look like” we are talking 100% identical. Misdirection?
The entire global genome Genbank database was scanned for matches. There were only 3 that matched all four sequences:
HIV
a bat corona virus discovered by Shi Zheng Li at WIV
SARS-cov-2
see around 24min:
https://www.youtube.com/watch?v=3bXWGxhd7ic&feature=emb_rel_end
If that was a homicide case you’d be on death row with that kind of evidence against you.
Shi has ‘disappeared’.
Study has serious problems. Most respondents were from the area immediately around Stanford Many zip codes had very few respondents. They only actually find 1.5% penetration, arrive at 3% by magic. Biggest problem in the study is mentioned in the paper itself. People might be more motivated to go to an opt-in test if they already had covid symptoms in order to confirm if they had it. This will skew the results because incidence if infection is likely higher among people who had the symptoms of the illness.
This study is useful for vetting the test itself but not particularly useful in knowing the actual penetration of the virus. Santa Clara County likely has a higher penetration rate that the rest of the country . So far 36,000 American deaths have been attributed to this and the likely number of actual deaths is probably 50% more than the attributed deaths due to people dying at home and people dying of it who did not have respiratory symptoms but the virus attacked the heart or kidneys or brain. So if the entire US were at 3% penetration and 36,000 have already died, we would need to be prepared for close to 800,000 deaths to get to the 70% penetration required for herd immunity.
Study may have some serious problems, but I think the most telling is the indication that the virus has infected 50 to 85 times the number tested. Anecdotal evidence has already pointed to this.
Let’s just look at my Metro area for some indication…
2018 flu season (CDC numbers)
Missouri, 1477 deaths. Covid 19 deaths- 159
Kansas, 630 deaths. Covid 19 deaths- 80
Where is your statistical evidence that this is the mass killer it has been positioned as?
What was the length of the Missouri and Kansas 2018 flu season? What was the length of the Covid-19 season? Were they over the same time frame?
“Study may have some serious problems, but I think the most telling is the indication that the virus has infected 50 to 85 times the number tested. ”
err no.
1. Skew sample due to recruitment bias
2. Suspect corrections for sex and race
3. Skew from including same household members
4. 1/3 of the 50 positive could be false positive by their own test metrics
It is a start. but jumped the gun.
fast, cheap, good
pick 2.
they picked fast and cheap
There was a need for fast. Additional seroprevalence studies will be coming perhaps weekly for awhile. I think the MLB one is next up.
yep.
and all of them will give different answers.
they have to.
and so all the testing will allow people to find their favorite answer and defend it.
as much as people think they want data to drive the decisions, the decisions
will be driven by hope and fear.
UK genetic researchers now think it has been spreading since sept/oct.
more uncertainty
I think we’re about six weeks to eight weeks out from a good set of studies of widespread, random seroprevalence, possibly with racial data.
Could ethnic Italians be more susceptible?
Also time series seroprevalence studies checking well categorized samples from six months previous to the present.
I mean big enough, well designed enough, studies most can accept.
But of course by then, events will have driven the decisions. Deaths or lack of.
Exactly right. Quoting:
Dying OF it, or dying WITH it?
800,000 is certainly a large number but there exist zero credible evidence suggesting that we’ll see that globally, let alone in just the U.S.
Dying WITH CV-19 means dying OF it, in the United States, at least 98% of the time.
Of course there are often comorbidities, but even when coronavirus is the straw (or anvil) that breaks the camel’s back, it’still what killed the camel.
Proving the fact that in the vast, vast majority of cases, dying with CV-19 means dying of CV-19 is just a matter of Arithmetic. About 7500 Americans die on an average day, when there’s no epidemic. COVID-19 currently infects less than 1% of Americans (probably), so of the 7500 who die of other causes we could expect that less than 1% (under 75) of them also happen to have COVID-19 infections. However, when people die of heart attack, stroke, suicide, murder, automobile accident, late stage cancer, etc., their death will not be attributed to CV-19. So only a fraction of those 75 deaths could plausibly be misattributed to CV-19.
A few dozen misattributions out of two thousand daily deaths hardly affects the statistics.
The UK death reporting distinguishes
Dying FROM: 86% or so
Dying WITH 14% or so.
Dying with means they would be dead anyway (with 30 days or so)
from their underlying co morbidity
Australia has the same situation because you have to have an official cause of death on a death certificate because it feeds into the legal, passport and insurance systems.
No, Steve, it does NOT mean that.
It means they died and tested positive.
Without it they might have struggled on for years.
Herd immunity is not a set magic number. It varies by organism. We’ll have to wait and see what it is for this virus.
It also assumes you can’t catch it again, that is a reasonably open question still with Covid19.
In the Netherlands an immunity study among 4000 blood donors revealed that about 3% of all population might have antibodies. The Netherlands have been testing very minimally: mainly at the hospitals. The estimated number of 3%, representing a half million of people, is about 16 times the numbers for positive tests.
This number (16 times instead of 50-85 times as mentioned in the paper) indicates a much longer way to herd immunity. And a higher risk for overwhelming the medical system in case social distancing diminishes. At present the ICU system in the Netherlands is working at 200%.
If not dying, people often need to be a long time in an ICU. Instead of an originally projected 10 days use of an ICU this modelled number had to be upgraded to 23 (!) days for the average patient.
Total expected death rate for all infected people is still somewhere between 1 and 2 %. Source (in Dutch): https://nos.nl/artikel/2330712-antistoffen-tegen-coronavirus-bij-3-procent-nederlanders-wat-betekent-dat.html
The research is going to be continued in the following weeks. Every week some 2000 immunity tests.
They may actually have missed the most interesting segment of the population: the above 80s. Very small probability that the nursing home inhabitants over 80 were on facebook this day and had the means to come to the test site. These people are stuck in close proximity to each other, continuously being exposed to nurses who bring covid in from the community.
“Study has serious problems. Most respondents were from the area immediately around Stanford Many zip codes had very few respondents. They only actually find 1.5% penetration, arrive at 3% by magic. Biggest problem in the study is mentioned in the paper itself. People might be more motivated to go to an opt-in test if they already had covid symptoms in order to confirm if they had it. This will skew the results because incidence if infection is likely higher among people who had the symptoms of the illness.”
weirdly the zip code map they publish doesn’t look like any Santa Clara zip code map I can find
But yes, There method of recruitment will give you a skewed sample
people who could not get a PCR test in the past but wanted one
Wonderful! Great idea! Hope it helps. Nice to hear about testing but I think the other “T”, TREATMENT, IS MUCH MORE IMPORTANT. What’s with testing if there is no treatment. HCQ has been shown effective but it is not controlled by BIG PHARMA. Be a helpful citizen and start treating.
Very easy answer. Test, if people are positive, then they’re isolated. Trace their contacts & test them. Wash & repeat.
Get the infected people off the streets, everybody else can get on with their lives.
HCQ hasn’t been shown to be effective.
Not a snowballs chance in hell that we are testing everyone every few days. We know from multiple places now that a very significant # of people have no symptoms. That means we would need to basically test everyone every few days to have any chance of stopping it. WE are going to run out of tests and materials to make tests long before we get to that. This thing is going to run it’s course. Thank God all indications are the IFR is relatively low.
One issue is they often isolate people at their homes and they infect the family members.
Adam Gallon: “HCQ hasn’t been shown to be effective.”
A doctor in a Texas nursing home reports the following:
135 bed nursing home, assumed full.
83 residents tested positive for Covid-19.
56 had symptoms (an assumption because 56 required a doctor’s care.)
The doctor treated either 39 of the 56, or all 56 (this is unclear, but I suspect all 56.)
Treatments started on Day 1 and every patient had started treatment by Day 4.
Treated all patients with a 5-day course of HCQ, an antibiotic, and zinc.
Around Day 12 he was interviewed and reported:
“Most” doing well and recovering. (Interviewer questioned him on “most”.)
One patient who is still in the home is going back and forth, but looking better, not worse.
Two patients transferred to the hospital, one because of a fall that needed treatment and one that needed treatment for dehydration because he wasn’t eating or drinking in his room.
If true, and none of 83 infected nursing home patients required a ventilator, an ICU bed, nor even a hospital bed for Covid-19 treatment and all are alive yet (this would be Day 16, I believe), then maybe HCQ is at least somewhat effective? Or are nursing home patients just generally resistant to Covid-19?
The news writeup on the above was terrible, so details should be questioned. But the results are surely of interest if what I wrote above is reasonably accurate.
What you will read of this when you find it:
1. Doctor is a Republican active in the party.
2. Doctor pulled strings to get access to HCQ
3. Doctor only had patient permission to treat 39 of 56 Covid-19 patients
4. Doctor may have treated patients without permission anyway.
5. Patients ended up in hospital anyway.
6. Patients were given risky, unproven, drug.
7. Patients needing HCQ for lupus, etc., had a hard time getting it due to use for Covid-19
8. Doctor is a Republican.
Disclaimer: The numbers I cite above are my best effort at dragging details out of some of the worst coverage of a story I’ve ever seen, particularly given the importance of the story. By now that recovering patient might have died or been hospitalized, for example. Or the dehydrated hospitalized patient could have been dehydrated because of Covid-19. Or the doctor could be flat out lying, etc.
“…..HCQ has been shown effective………”
HCQ gave initial indications that it might be effective. So far, follow-up trials have shown mixed results, so, even if it does have some effect, it’s probably not a major cure. That’s probably the best you can say so far – further trial results may change this, of course…
U of Calgary just launched an interesting trial focusing on the proper role of HCQ, i.e. early dosage to prevent severe symptoms.
“The “HOPE” trial, to begin April 15, will target 1,600 Alberta outpatients who have tested positive for COVID-19 and are at risk of developing severe symptoms. The study will determine if hydroxychloroquine can prevent hospitalization for those at highest risk of developing a severe illness.
Participants will give their permission to Alberta Health Services after testing positive for COVID-19 and provide their contact information to U of C researchers. They’ll then be screened for safety and eligibility through a telephone interview and review of their electronic health record.
Those patients accepted will be sent hydroxychloroquine to their homes and will be required to take the drug over a five-day period. Researchers will follow up with participants seven and 30 days after starting the treatment.
Metz said timing of the trial is crucial and must begin within 96 hours of confirmation of a positive COVID-19 result, and within 12 days of symptom onset.”
Announcement is here: https://calgaryherald.com/news/u-of-c-researchers-to-begin-hydroxychloroquine-trial-on-covid-19-patients/
My synopsis is https://rclutz.wordpress.com/2020/04/15/canada-bends-the-curve-april-15-update/
I would like to see study where people given drug as soon as test comes back positive and test results come back within 48 hours of them first requesting to see a doctor.
In Canada often there is a lag between wanting to see doctor and then actually seeing the doctor. Then another lag period for test to be done.
That Alberta “test” seems a totally half-arsed effort which is so loosely done it will not prove anything either way.
“and within 12 days of symptom onset.” If you are not in hospital by day 12 you don’t need anything !
No mention of a control group ? How will they know whatever result they get shows an effect of HCQ or not?
This is garbage.
Totally agree Gregg. Seems like ridiculous, useless study. Except useful for Big Pharmaceuticals.
Wrong … It’s worthless to Big Pharma. By Big Pharma standards, there’s no money in Hydroxychloroquine.
actually there is a study in Brasil, where they gave HCQ and azythromycin to 412 patients at the second day of showing symptoms, but not yet having a positive test result. They also had a control group of 228 patients not taking it. First results saying that there is a reduction of 60% of deaths. Study was submitted to PLOS Medicine.
Thanks.
HCQ without supplementary zinc much less effective. Needed dose, according to one doc is 220 mg zinc per day. That is about 7 times a daily “supplement”. The workhorse is the zinc. The HCQ opens the door for cell entry. The virus is targeting the red blood cells. Oxygen deprivation follows, with sickle cell, worse and sooner, hence the heavy breathing and heart attacks. This is followed by a cytokine storm which give the lungs chemical pneumonia. The early treatments were for viral pneumonia. Oops.
It appears Hamilton Health Services will start the HCQ+zinc study this month:
Experimental: Azithromycin and Chloroquine Therapy (ACT)
Chloroquine (Adults with a bodyweight ≥ 50 kg: 500 mg twice daily for 7 days; Adults with a bodyweight < 50 kg: 500 mg twice daily on days 1 and 2, followed by 500 mg once daily for days 3-7), plus Azithromycin (500 mg on day 1 followed by 250 mg daily for 4 days)
https://clinicaltrials.gov/ct2/show/study/NCT04324463?cond="Coronavirus+Infections"&draw=3&rank=11
Correction: That’s an antibiotic, not zinc.
I wonder why they have chosen chloroquine and not hydroxychloroquine. That stuff has nasty side effects.
What is the chance anyone has already a known contra-indication to chloroquine ? No has been given this stuff for years because of its nasty side effects.
They do not even check for existing heart conditions ! What are they trying to do here, ki11 a few more patients so they can discount Raoult’s hydroxychloroquine protocol by deliberately ignoring it.
Looks like more designed to fail “tests”.
FFS, they should have said “only male or female”. Risk ki11ing your patients but make sure you are politically correct about who can apply.
Since I cannot use the information, EVEN THOUGH IT IS OUT THERE AS IF I COULD, I cannot comment on it, because, I suppose, in order for my comment to have any validity, it has to apply to a peer reviewed article, and so, until such time as the study is peer reviewed, I withhold any comments, since they would be worthless, EVEN THOUGH THEY WOULD BE OUT THERE.
QUESTION: Why publicize an article deemed to be unworthy, until peer reviewed? Really, what’s the point, if the information cannot be trusted and used. Just keep it out of view, until such time as it becomes worthy. Otherwise, the gesture of putting it out there contradicts the disclaimer.
Boston homeless shelter tested 397 people & 146 tested positive for WuhanFlu. Yet none, repeat none, had symptoms.
USA vessel T. Roosevelt sailors were tested for WuhanFlu. Among those testing positive 60% had no, repeat no, symptoms.
In the BHS article after being moved to an isolation facility some developed symptoms including the need for hospitalization. So for some there is a progression from asymptomatic to symtomatic.
Hi chemman, Barbara McInnis House is where the positive testing Boston homeless cases were brought. I can find no update on-line that there were subsequent acute case hospitalizations.
My search engines keep showing the report from yesterday, so maybe you’ve an update source to share. I can believe asymptomatic cases will progress to symptomatic.
Homeless people with positive test: 0% with symptoms.
Navy people with positive test: 40% with symptoms.
Either homeless people are much more resistant to covid-19 than sailors, or there are extremely different strains of covid in Boston vs. the USS T. Roosevelt, or something’s seriously wrong with one or the other study. I’d bet the latter (probably either different kinds of tests, but maybe different definition of “symptom”–like fever of > 102 vs. fever of > 100, or such like).
It comes down to how many virus particles enter your body to attack your system. Homeless live in an open airy environment. Sailors live in berthing quarters where the air is not circulating as much.
Breath in just a few virus strands and your body can fight them off. You have antibodies in your system which show up on tests.
Breath in more virus strands and your body might still fight them off but your system is affected more so you show symptoms.
So we need to turn ball fields into covid-19 wafting areas?
Setup misters (etc.) with a very low density of covid-19 virus and have large numbers of people walk through the mist.
The ball parks have large amounts of parking and are sitting empty waiting for a use.
The first port of call, in epidemic influenza penetration happens to be the children and the homeless.
None seem to show symptoms like the rest.
Maybe because this is not the first time around for these groups…
Maybe!
How many children have being tested in comparison with adults?
Wondering what an antibody test result will be in consideration of a children group, like in an area of NYC… or London.
Just saying.
cheers
If I understand the medical science, this is a better antibody solution that uses a medical science breakthrough, that has already been tested.
This research is also San Diego based.
The breakthrough was figuring out a method to cheaply and very, very effectively to evolve antibodies that had been developed in the past to fight new emergencing viruses.
The researcher, Jacob Glanville, who discovered, how to evolve antibodies cheaply and very, very effectively, has a dozen other medical revolutions. This same technique can be used to develop optimized antibodies to attack cancer in a person’s body.
He is the person that helped solve the virus simulation problem which opened up an entire new field of medicine. This new technology (computer evolution of designer viruses) was explained along with a interview with Glanville on the HBO documentary on the risk of AI.
This new technology enables viruses to be modified so they can work as nanobots in the body. The nanovirus are injected into the body, and as the viruses are evolved to enable them to evade the immune system, they then reproduce, do something good, and then die.
He is also working on a universal vaccine.
He has also developed microbiological systems that drastically reduce the cost, time, and risk to produce drugs and to produce new drugs.
The non profit, for people medical science industry, spent two years and lots of money to develop optimized and safe antibodies for SARS.
The problem is we got covid-19 not SARS.
This researcher developed a microbiological system that evolved five SARS antibodies that were developed, to enable the SARS antibodies to learn how to attack the Covid-19 virus.
The evolved covid-19 killing antibodies have been sent to the US Army Medical Research Institute of Infectious Diseases where tests with animals and live virus will be done. If all goes well, human tests will start in August.
“I’m happy to report that my team has successfully taken five antibodies that back in 2002 were determined to bind and neutralize, block and stop the SARS virus,” Glanville told the Radio New Zealand program “Checkpoint.” “We’ve evolved them in our laboratory, so now they very vigorously block and stop the SARS-CoV-2 [COVID-19] virus as well.”
Interview with Fox:
https://www.foxnews.com/media/dr-jacob-glanville-antibody-neutralize-coronavirus
Description of the microbiological science.
https://nypost.com/2020/04/01/doctor-in-netflix-doc-says-he-discovered-potential-coronavirus-cure/
Researchers — aware that COVID-19 “is a cousin of the old SARS” — created “hundreds of millions of versions” of antibodies for that virus, “mutated them a bit, and in that pool of mutated versions, we found versions that cross them over,” Glanville said on the radio program.
William Astley
April 17, 2020 at 12:35 pm
The best antibody for COVID-19 is the COVID-19 antibody.
A considerable dose of any other antibodies will suppress, at least temporarily, the COVID-19 antibody
response, in the people that already have got it… leading also to time extension for the possibility of acquiring it from those who do not have it, and delaying the proper response from the herd.
And that ain’t pretty, in consideration of a disease period… or reemergence.
Is like administering the wrong vaccine at the high of a disease period.
Causing an unnecessary dysrhythmia of the condition.
Antibodies do not kill viruses, not directly at least… and at the high of a disease the efficiency of the antibodies consist as the efficiency of harmonious quick sharp “wash out” of the virus overload from the system.
It is that efficiency that boosts and keeps overall immunity to a disease at the best standard.
A wrong antibody at some point got to get “washed out” too from the system, especially in the consideration of the disease… consisting as a delay to the proper response
Even an external extra (high) dose of COVID-19 antibodies can jeopardize to a degree the efficacy of the immune system response to COVID-19 for a while…
non effective for people who already have the antibodies in their system.
cheers
I am not 100% sure, but the research similar to what you have described has already been used to treat some form of cancer (lymphoma). It uses virus vector to modify white blood cells (T cells) so they can recognize cancer cells as a target. It is not my area of expertise, so take this information with the “grain of salt”. The technique (named CAR) was initially developed in USA but was very expensive – about 0.5 million $ per treatment. Lat year team at Westmead Hospital Sydney developed similar technique for a fraction of cost – about 10,000 $ per treatment. They reported successful treatment of the terminally sick 18 year lymphoma patient in May last year.
Conclusion:
The test has 5% false positive outcome.
New paper out this week in Int J Infectious Diseases* shows very low infectivity, with an R0 of less than 1.14 based on the Diamond Princess cruise ship data. It was originally estimated and widely disseminated in the media that the virus had an R0 of 5-7. SAR-COV-2 has a much lower than even H1N1.
The T. Roosevelt data tracks closely with the cruise ship data, and these excellent experiments in confined humans are mutually confirmatory, even though one population is young, and the cruise ship passengers were old (mean=58 yrs).
*International Journal of Infectious Diseases 93 (2020) 201–204
“The T. Roosevelt data tracks closely with the cruise ship data, and these excellent experiments in confined humans are mutually confirmatory, even though one population is young, and the cruise ship passengers were old (mean=58 yrs).”
The excellent experiments in nursing homes suggest a much larger R0!
why? why is this?
why?
R0 is NOT an inherent property of the Virus.
R0 is NOT an inherent property of the Virus.
R0 is NOT an inherent property of the Virus.
R0 is an EMERGENT metric of
A) the transmissivity of the virus
B) the pattern and nature of human contact with other humans
C) the pattern and nature of human contact with public surfaces
D) the hygienic practices of the humans in question
Now for simplicity sake people just talk about R0 as if it was an inherent property
of the Virus. It’s not.
Put another way. In the wild you will get
1. 100 cases where the infected person, infected 1 more person. (R0=1)
2. 1 case where the infected person infects 100 (R=100)
final answer 101 cases leads to 200 R0=2.
The final R0 is always a composite of many cases where the pattern and nature of human
is different
AIDS has a R0 of ZERO if you avoid certain activities, for example.
I did not say it was an inherent property. Of course infection relies on environmental constraints, Captain! I agree with you on the reality.
…now getting to the practical.
I can think of only two main things that may impact the transmissibility, infectivity, or lethality to the extent we see in the two experiments:
1) The virus is not inherently lethal. This may be, since there are at least 6 recognized and sequenced coronaviruses in circulation today. These are types of the common cold, along with rhinoviruses in the main, and other cold viruses (RSV, Pseudo, Para, etc.), for which the overwhelming victims recover without serious sequelae.
2) There exists already in the population, some degree of immunity. This possibly is happening because either the virus has been around longer than we think as SARS-CoV-2 itself, or another virus (like SARS-CoV-1 from 2003) which conferred a cross immunization, because of similar epitopes presented to our immune systems leading to recognition by Thr cells and other surveillance cells. This latter has corroboration, in that the Stanford vaccine is based on already manufactured batches in response to the SARS 2003 breakout.
Coronas have probably been around for ages, occurring cyclically, as naïve population develops generationally.
Steven Mosher
April 17, 2020 at 5:22 pm
Now for simplicity sake people just talk about R0 as if it was an inherent property
of the Virus. It’s not.
Put another way. In the wild you will get
1. 100 cases where the infected person, infected 1 more person. (R0=1)
2. 1 case where the infected person infects 100 (R=100)
final answer 101 cases leads to 200 R0=2.
The final R0 is always a composite of many cases where the pattern and nature of human
is different
————————————-
Ok, I get it now.
R0 is an EMERGENT metric of
a) life (infection)
b) death (detection, confirmation of infection)
C) a certain infection… from a certain virus… with certain inherent properties.
and an inherent property of numbers… or persons… or the environment…
aha we getting there.
I think I got it right.
Have I!!!!
Mosh?
cheers
Mockton and jo anne nova watch out you may be held responsible for the death of millions due to stupid lockdowns (you wont be held responsible its a joke) but you should not post anymore about lockdowns working because you know nothing about viruses they will infect everybody its just the f**** cold virus thE UNITED STATES IS HAVING A REVOLUTION JUST LIKE 1770 AGAINST THE BRITISH EMPIRE JUST watch minnesota now . That why The USA Left the british pompous British royalists gits like you Mockton you publish crap aboput a 1.5c increase in temperature you have lost all credibility it may be -1c what a joke i wish you the best I want my children to have a life I am 68 you dont seeem to give a s@@@ about you children please dissapeare from this site
Please take our own instruction.
Eliza quit projecting and drunk posting, you’re not terribly intelligible at the moment.
I agree I WAS DRUNK but Willis was correct sorry AS he is always re the coronavirus hyper. As you may recall, I said that Sweden would NEVER have the deaths projected by the IHME model used by the US government. As shown above, on the 11th (6 days ago) they said 13,000 deaths. On the 14th (3 days ago), they said 18,000 deaths. Here’s the same graph as above, but with a standard non-logarithmic y-axis. look it up he WAS COMPLETELY WRONG
I agree I was drunk but look at the data the guy is completely wrong i am only trying to save lives of unemplyed of billions worlwide for what is a normal cold flu virus look up recent University of chicago tests the incidence is about 50 higher so mortality is extremely low compared to normal flu
You do realise that high blood pressure is a risk factor for covid19?
https://www.gov.uk/government/statistics/weekly-all-cause-mortality-surveillance-2019-to-2020
Check out the spike in deaths, about 10,000 more than normal last week (10thApril), about 6000 the week before, this week will be upwards of 10,000. The difference with daily published figures is the many who have died in care homes or at home who never got a covid19 diagnosis but died anyway. I’m hoping that next week deaths start to fall but cases are still rising in care homes. All those deaths from a cold? Or was it Easter chocolate toxicity? Those figures are after basic social distancing with regular handwashing, closure of mass gathering and finally a mass lock down.
We really don’t know yet how many have had it and there may be many silent cases… then again there might be only a fraction of the popuation. There is also a growing possibility that silent cases don’t sustain enough antibodies to avoid catching it again. While those people might still avoid sickness, they could keep the virus circulating freely until there is a cure or a vaccine.
The study misses one important control: people who caught a cold recently but were negatively tested for SARS-CoV-2.
So in other words, this isn’t any worse than the flu and the inflated severity of this can be considered a hoax by media. Seriously, think about it. Democrats don’t want to reopen the economy. Democrats don’t want to talk about hydrochloroquin (likely spelled wrong) even though the whole world supports it. The Democrats want to rely on the “experts” even though the “experts” have been wrong… And wrong… And wrong…
And the experts have vested interests, both economically and fame-wise.
The common element for three different treatments that work is the suppression of the cytokine storm creating chemical pneumonia. The three are:
– Hydroxychloroquine plus zinc and azithromycin
– hydrogen gas (H2) 5% with oxygen
– Ivermectin plus zinc plus azithromycin
All three regimes target the production of free radicals. See one very good cell-by-cell explanation (it is a bit technical so get a pencil).
https://youtu.be/-oh9Ztgjm4A
Ivermectin is no good. I just did an analysis for a government agency about the viability of Ivomec for Sars-Cov-2, by analyzing the recent. The Australian study is not worthy. I took this Jans study and calculated that the antiviral in vitro study used concentrations hundreds of times the concentration in blood in humans from a normal Ivomec dose. Hundreds of times the normal dose in humans is more than an order of magnitude 100% lethal.
Also, I think the Zinc and HCQ is superfluous. AZT is an antibacterial, and very effective alone against lethal concomitant bacterial infections.
We have to be concerned with sensationalistic studies in the popular “science” media.
Caveat emptor!
(And as the late philosopher Stan Lee has said, “Excelsior!)
And the Democrats are trying to change the voting process.
Meanwhile in the “good news .. sort of” department:
Professor Luc Montagnier, has a positive turn. According to him, the altered elements of this virus are eliminated as it spreads:
“Nature does not accept any molecular tinkering, it will eliminate these unnatural changes and even if nothing is done, things will get better, but unfortunately after many deaths.”
https://www.zerohedge.com/health/covid-19-man-made-virus-hiv-discoverer-says-could-only-have-been-created-lab
It is already easy to tell by the posts here that the populations overall response to this is hysterical. I truly believe the mass media has overblown all of this by massive proportions. My personal bio-history suggests that I should be dead now. Guess what?, I’m still typing. :-p
Geez if you want to prevent deaths ban food stamps being used for junk food. Invest the trillions lost from these lockdowns in early cancer detection, literally pay people to have colon and breast cancer screening. It would be way cheaper.
As far as I can see, he doesn’t specify the source of his lateral flow immunoassay test devices.
My guess is that since this is not work connected with treatment of seriously ill patients and their contacts, he is using the Chinese devices.
The UK tested these and found them very inaccurate, giving around 10% false positive results for the batch tested. If this paper is based upon Chinese test devices, it is possibly not worth the paper it is printed on.
From Fox News this afternoon:
“However, as with the case for any test, accuracy does remain a concern, Segal said. The Premier Biotech serology test, which was used in the Santa Clara County study, has not yet been approved by the FDA.”
Same info coming out of Europe now.
No need for lock down.
Of course there are some that want to quarantine everything on a whim!
“In a 1987 article for The American Spectator, “AIDS: A British View”, Monckton argued “there is only one way to stop AIDS. That is to screen the entire population regularly and to quarantine all carriers of the disease for life. Every member of the population should be blood-tested every month … all those found to be infected with the virus, even if only as carriers, should be isolated compulsorily, immediately, and permanently’
He had a point. If this had been done, potentially millions of sufferers could have avoided AIDS completely. This is indisputable.
The question of whether restriction of the freedom of a few, compared to the freedom from infection of a great many, is one that is not easily resolved. In hindsight, I think many may have agreed with him, but a lot are dead now.
with three million dead from communicable diseases since the beginning of the year that is a lot of people to keep locked down if we follow this procedure.
This is a typical good news – bad news story but not unexpected. I am an infectious disease physician and am pleased to start seeing serology surveys which will give us a much clearer view of this epidemic. This paper suggests (good news) a much larger population have been infected with the virus and stayed well throughout. That translates to a much lower morbidity/mortality than is commonly quoted. Chances are mortality is a fraction of a percent if other surveys show the same result. The bad news is that a much larger population has been infected meaning that attempts to prevent spread of the virus have not be anything like as effective as many believe. In the end it may turn out that many fo the very restrictive measures undertaken and the high costs they entailed were not effective and therefor not justified.
More good news is that, if measures to reduce transmission are really not that effective, CoVID still only infected a maximum of 4-5% of the population and we won’t know why it seems to plateau at that level with current information. This could explain a picture I see in Europe with several different countries having different shaped curves seeming to reach plateaus of cases and deaths that proportionate to age-standardized populations are actually quite similar.
So much more to know and time will shed a much brighter light on this eventually.
Andy Pattullo: “we won’t know why it seems to plateau at that level with current information”
WR: It might be that as soon as the virus manifests itself, the fear for the virus leads spontaneous to a lot of social distancing which stops a full speed spreading. Apps to inform people might create ‘the right quantity of social distancing’, diminishing the need for interference by the government.
There are still many differences within countries. ‘Carnaval regions’ in the Netherlands (the southern part) and Germany (the western part) are well recognized: a high percentage of Corona cases. Densely populated cities and transport hubs with a lot of international contacts score high as well. In the same time we find on the country side ‘Corona empty locations’. Will the virus spread evenly over a country over time? Will ‘a next round’ hit other parts of a country? As long as the virus is still active it can pop up everywhere.
The good news is indeed that the virus more often passes without big problems for the people involved. And all people with antibodies will slow down future spreading. Really good news.
A big question that remains is about the different strains of the virus that developed. Are there strains that are more lethal than others? Do we get a certain ‘selection’ of less lethal strains of the virus by isolating all people with more severe symptoms? This could influence the requested policy.
“A big question that remains is about the different strains of the virus that developed. Are there strains that are more lethal than others? Do we get a certain ‘selection’ of less lethal strains of the virus by isolating all people with more severe symptoms? This could influence the requested policy.”
all strains ( 10 clade last I looked) seem equally deadly, or rather there is no evidence to suggest
otherwise. The rate of mutations suggest a virus that is happy with its host.
easily spread, and no too deadly. deadly enough to frighten the host, but not so deadly as to to kill
them all and spoil your chance to multiply. Happy virus in the Goldilocks zone!
no evolutionary pressure to change anything
That should be the good news which means we can stop this stupidity right away and stop destroying our own lives.
As a wise man once said : There is nothing to fear but fear itself.
As others have pointed out, there is a belief that there is currently no reliable and specific test for Covid-19 antibodies.
However, the findings do not surprise me because the virus is obviously highly infectious and does not always produce symptoms of infection. It would be a good result if true.
On 4/4 Santa Clara County was reporting 1148 cases. As of yesterday 4/16, 65 deaths. If between 50 and 85,000 are infected, death rate is miniscule.
If less than 5% have been infected, and therefore more than 95% are still susceptible to infection, then up to 20 times the actual deaths are likely to eventually occur, which is to say 65×20 = 1,300 in Santa Clara County and if the same percentage applies for the whole US, something like 640,000.
So how is this good news? Do you think that there’s an upper limit on who is susceptible to infection? If not, why is the number of new cases declining? If not social distancing then what? Is it spring arriving (btw 1-5 inches of snow forecasted for tonight in CT). If it’s weather, then it will certainly be back in the fall.
I hope I’m missing something big.
Maybe it’s not as transmissible as feared. Increase in number of new County cases has been basically linear since this survey was done, not geometric. Compund growth rate over last four and seven days <4%
The common belief that 100% of the population are susceptible and likely to get infected is not based on our experience with most outbreaks. Immunity from prior infection is only one of the factors that prevents infection. There are likely many unknown genetic factors and other poorly understood behavioural and contextual factors which play a role. Viral infections that generate infections and later serologic immunity in the whole population or a very large proportion of the population are uncommon and are typically highly adapted to humans through long co-association. Examples include cytomegalovirus (CMV) and chickenpox (varicella) two fo the numerous herpes viruses. This is why I mention we don’t fully understand the limits of penetration into a population and it is unwise to model an epidemic assuming 100% of the population are likely at risk. It works well for science fiction movies but doesn’t resemble the real world. As another example smallpox, a devastating disease was estimated to have a 30% mortality rate but maximal population death rates in the worst years were 0.3-0.7 % suggesting only 1-2% of the population were infected each year ins lite of it being a highly infectious virus.
We can’t pretend we know all of what we would like to know about the dynamics of viral epidemics, but if we keep open minds we will gradually learn more.
Andy,
If anybody around here is keeping an open mind and not adopting a pet hypothesis, it has been me. I have tried to hold back on speculation as much as possible. I was skeptical that social distancing was working. Secretly I hoped to see 40% immunity from massive numbers of non-symptomatic cases, but I didn’t predict it and I continue to integrate new facts as they appear.
There still needs to be more testing before I will be willing to settle on a confident conclusion.
I agree that it’s possible that I am misinterpreting the new data. It’s logical that not everyone is equally susceptible. It’s possible that sars-covi2 is seasonal. Those are known unknowns. It’s likely that there are other factors that we haven’t even considered. But the simpler answer is that less than 5% have been infected and many more are susceptible. I’m a fan of Occam’s razor.
It’s not panning out as I hoped. This makes it all the more vital to have effective therapies.
At this point the data says to me that it is more likely than not that we will see a spike in cases when we relax social distancing. We need to try it anyway, to hopefully prove that wrong, because if we destroy the world economy, that will be worse.
Upon reflection, the number of known cases in Santa Clara was a very low proportion of the general population. That makes sample size and random selection all the more crucial.
If by luck, despite the miserable methodology thoroughly discussed by Steven Mosher, they still managed to measure the ratio between actual infections and known cases relatively accurately, then 50-80:1 is good news for areas that have already been through a peak such as metro New York.
In the US at the time I write this, there are 710,272 confirmed cases. The optimistic 80x would be 57.8 million people out of 328.2 million who may have immunity. 18% of the US population—very far from, less than a third of the way, toward the 60% minimum thought to be needed for herd immunity.
But in New York there are 233,951 confirmed cases. At the optimistic 80x ratio, that represents 18.7 million total infections in a state population of 19.45 million (96%!)
Now that’s in effect dividing cases that are mostly in the NY state portion of metro NYC by the total population of NY state. What if you add together NY, NJ, and CT cases and divide by metro NYC population of about 21 million?
NY 233,951
NJ 78,467
CT 16,809
Total 329,227
329,227 x 80 = 26,338,160
which is 125% of the metro population, obviously wrong.
So let’s go at it from the other direction. What does the ratio of total:confirmed cases need to be in metro NY to achieve 60% (herd immunity)?
60% of 21,045,000 = 12,627,000
12,627,000 / 329,227 = 38.4
38.4 is well below the result found in the badly flawed Santa Clara study (50-80)
So, it seems to say, contrary to popular perception, that the FIRST place in the US that could safely go back to normal would be metro New York.
If you’re in San Jose, it’s miserable news because apparently you’re at best looking at 5% immunity. (Maybe only 1.5%). Do you stay in lockdown or open up and become the next metro New York?
If you’re in another densely populated metro region that has so far avoided trouble, you too get little comfort from this study.
But maybe it’s seasonal (I say as I watch the snow falling in my back yard). Maybe those who avoided NY’s fate are safe until October.
We can hope.
stanford hospital is empty
I posted a video on this the other day.
Everything about this virus is LOCAL.
As of early 2020, humanity is confronting a pandemic in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). SARS-CoV-2 causes coronavirus disease, abbreviated as COVID-19. At the time of this writing, SARS-CoV-2 is spreading in multiple countries, threatening a pandemic that will affect billions of people. This virus appears to be a new human pathogen. Currently there are no vaccines, monoclonal antibodies (mAbs), or drugs available for SARS-CoV-2, although many are in rapid development and some may be available in a short time. This Viewpoint argues that human convalescent serum is an option for prevention and treatment of COVID-19 disease that could be rapidly available when there are sufficient numbers of people who have recovered and can donate immunoglobulin-containing serum.
https://www.jci.org/articles/view/138003
The most vulnerable people seem to be those in Nursing Homes, so they should be getting this preventative as a priority..
Thanks Anth*ny, this is the best place to go for accurate, unbiased info on the pandemic. You & your contributors should be paid millions — the fake-stream media gets more than that for fake news, lies & propaganda.
I don’t think that this is good news at all if less than 5% have antibodies. To me that says first of all, more than 95% of the population is potentially still susceptible to infection and possibly vulnerable to serious complications or death. We are maybe only 1/12 of the way toward herd immunity IF this test is accurate and representative of the rest of the country.
Those who would argue that social distancing was ineffective would need to explain why such a small percentage have antibodies. This result is only a third of the disappointing Gangelt Germany results.
Now the optimistic spin would be that only 5% are susceptible to covid-19 infection in the first place (which requires the conclusion that the Gangelt study was invalid due to false positive tests), and social distancing was ineffective so that nearly all the susceptible got infected. Not plausible to me. Much more likely that similar social distancing across western populations yielded similar suppression of infection. Ignore whether there was an edict, most people acted autonomously to reduce contacts (including Sweden where many live alone). Korea did better with a well-prepared surveillance testing program. If that hypothesis is true, the same kind of serology test in Korea should find significantly lower antibodies.
No my friends, while it would be wise to wait for broader testing, and assurance that the test is valid, this is not the answer I hoped to hear.
I replied above to your similar comment. It would be extremely unusual if 100% of a population had equivalent susceptibility to a new human viral outbreak – except in Hollywood. We have no idea if social distancing is making a difference thought there is certainly logic to say it may, but without understanding all the other factors that affect susceptibility we just don’t know. There are clearly places where social distancing either can’t or won’t be in place – let’s see how their numbers turn out. I expect still only a small proportion of the population develop immunity – I may be proved wrong.
I devoutly hope that you are right and I am wrong.
If a there is a much higher number of infected and remdesivir really does work then this disease mortality is less than the flu.
Stevek,
On what planet is 1.5-5% of the population a much higher number of infected? You mean compared to 0.03%?
At the low end of the range with only 1.5% infected, 98.5% are potentially still susceptible. That means potentially 67 times the current death toll over time if we don’t have a vaccine or effective treatment. And that would be 4,333 deaths in Santa Clara county, 2.1 million in the US.
I used to entertain the thought that Trump talked about “up to 2.2 million deaths” to make us think an unnecessary lockdown was justified. Not so much anymore.
@Rich Davies
I completely agree.
Given all the available numbers so far, going the path of herd immunity is just a monstrous euthanistic project.
And these are numbers one can actually predict because there is real data. Still big uncertainties because of the quality of the data but at least not total made up assumption-driven models how many will die because of the lockdown.
I have three words for you; Italy, Spain, and Ecuador.
If the infection rate is 75% in the sample area and the medical facilities were not overrun, we must conclude that the infection rate. In parts of this country are higher.
If surviving the infection imparts immunity, why are Italy and Spain experiencing an increase in deaths after easing restrictions?
Wait, how do you arrive at 75% infected based on less than 5% with antibodies?
Oh Christ
They, allowed the subjects to bring a child from the household
~900 of the 3500 subjects are from the same household
80% of case transmission is family to family
BZZZNT
overestimates the prevalence
Huh?
Plus motivation from people who got symptoms but couldn’t get a PCR test around that time might be higher to self-register for being tested.
That’s a problem with non-randomized subjects.
YUP
here is a peer review, says the same thing
https://medium.com/@balajis/peer-review-of-covid-19-antibody-seroprevalence-in-santa-clara-county-california-1f6382258c25
Thanks for the link, very informative!
I should pay more attention to the confidence intervals in the future. Always slips my mind especially if I already see non-statistical confounding problems with the study design or its interpretation.
alice: One of my kid tested positive in feb, can we get tests for the whole family?
Doctor: No severe symptoms no tests.
Alice: but we are in contact daily!
Doctor: sorry CDC rules, no severe symptoms,no test, fly to Korea if you want to be tested.
…..
jane: hey Alice, they are doing antibody testing, did you see it on facebook?
Alice: no let me check, oh wow, I can go get tested and bring one of my kids
jane; ya, you can find out if you had it when they refused to test you, call your friends
let them know, everyone from our coffee group should go and bring their kids.
Result? Non random sample .
“The test kit used in this study (Premier Biotech, Minneapolis, MN) was tested in a Stanford laboratory
prior to field deployment. Among 37 samples of known PCR-positive COVID-19 patients with positive
IgG or IgM detected on a locally-developed ELISA test, 25 were kit-positive. A sample of 30 pre-COVID
samples from hip surgery patients were also tested, and all 30 were negative. The manufacturer’s test
characteristics relied on samples from clinically confirmed COVID-19 patients as positive gold standard
and pre-COVID sera for negative gold standard. Among 75 samples of clinically confirmed COVID-19
patients with positive IgG, 75 were kit-positive, and among 85 samples with positive IgM, 78 were kitpositive. Among 371 pre-COVID samples, 369 were negative. Our estimates of sensitivity based on the
manufacturer’s and locally tested data were 91.8% (using the lower estimate based on IgM, 95 CI 83.8-
96.6%) and 67.6% (95 CI 50.2-82.0%), respectively. Similarly, our estimates of specificity are 99.5% (95
CI 98.1-99.9%) and 100% (95 CI 90.5-100%). A combination of both data sources provides us with a
combined sensitivity of 80.3% (95 CI 72.1-87.0%) and a specificity of 99.5% (95 CI 98.3-99.9%).
ouch,
WRT to allowing people to bring their children.
dumbass test design.
‘ After weighting our sample to match
Santa Clara County by zip, race, and sex, the prevalence was 2.81% (95% CI 2.24-3.37 without clustering
the standard errors for members of the same household, and 1.45-4.16 with clustering). ”
why? why make your analysis harder by including close contacts.?
same with the adjustments for race/sex.
why? The enrollment process would allow them to accept enrollees in such a way that
you got representative samples with no need to adjust the data.
Consistent with ZERO.
“These results represent the first large-scale community-based prevalence study in a major US county
completed during a rapidly changing pandemic, and with newly available test kits. We consider our
estimate to represent the best available current evidence, but recognize that new information, especially
about the test kit performance, could result in updated estimates. For example, if new estimates indicate
test specificity to be less than 97.9%, our SARS-CoV-2 prevalence estimate would change from 2.8% to
less than 1%, and the lower uncertainty bound of our estimate would include zero. On the other hand,
lower sensitivity, which has been raised as a concern with point-of-care test kits, would imply that the
population prevalence would be even higher. New information on test kit performance and population
should be incorporated as more testing is done and we plan to revise our estimates accordingly.
jesus what a mess.
Age distribution is the critical parameter to control for in the sampling.
Age distribution is the critical parameter to control for in death stats as well.
‘This study had several limitations. First, our sampling strategy selected for members of Santa Clara
County with access to Facebook and a car to attend drive-through testing sites. This resulted in an overrepresentation of white women between the ages of 19 and 64, and an under-representation of Hispanic
and Asian populations, relative to our community. Those imbalances were partly addressed by weighting
our sample population by zip code, race, and sex to match the county. We did not account for age
imbalance in our sample, and could not ascertain representativeness of SARS-CoV-2 antibodies in
homeless populations. Other biases, such as bias favoring individuals in good health capable of attending
our testing sites, or bias favoring those with prior COVID-like illnesses seeking antibody confirmation are
also possible. The overall effect of such biases is hard to ascertain.
The Premier Biotech serology test used in this study has not been approved by the FDA by the time of the
study, and validation studies for this assay are ongoing. We used existing test performance data to
establish a range of sensitivity and specificity, including reliable but small-size data sourced at Stanford.
Test sensitivity varied between the manufacturer’s data and the local data. It is possible that
asymptomatic or mildly symptomatic individuals may generate only low-titer antibodies, and that
sensitivity may be even lower if there are many such cases.23 Additional validation of the assays used
could improve our estimates and those of ongoing serosurveys. ”
1. the age bins reported are stupid. 0-4, 5-18, 19-64, 65+
why?
2. Positive rates are not reported Per Age bin.
Thanks Steven,
Being a resident of Santa Clara and an amateur number cruncher, this study’s results seemed contradictory to everything else virus-related I have been absorbing since Jan. 17. Your link to the review helped me understand why it may be almost worthless in describing the current local situation in regard to COVID-19. It is highly appreciated and will be shared with the many people I have been communicating with about this for three months. Innumerancy is a contagious disease itself, and the many subtle possibilities and clear explanations offered in this review help vaccinate me against the wild misunderstandings I see in so many comments.
There may be some things that “rescue” the results, but they need to release more data
I would like to see their recruitment criteria.
A) did they tell the subjects that they would NOT tell the subject whether they tested
positive or negative? this would ameliorate the selection bias
B) did they ask the subjects if they had
1. had any symptoms whatsoever
2. Know anyone who was tested
3. worked in a high human contact service job
4. Requested a PCR test in the prior 3 months and been denied
That might make me more accepting of the results, but they do not document their recruitment
protocal.
This is not that hard to do.
Ok
here’s a professional, detailing the issues
https://twitter.com/nataliexdean/status/1251309217215942656
Be careful finding what you want to believe
Good advice to share with your warmista friends, too, Steven.
I share it with everyone.
People who find a station adjusted poorly
People who find a really hot day, or really cold day
People who look at just one country (USA) for their temperature data
People who look at models that run really hot, or cold
People who only look at UAH
people who look at photos of subs at the north pole.
people who look at one tree in Yamal
The tendency to find what you want to find is pervasive.
so when a skeptic finds a warmist who finds what he want to believe
the skeptic has found what he wants to believe
and vice versa
Gotta lurve your postmodern approach to the truth Mosh, ‘The truth is what people believe it is’
Until you find yourself gasping for breath in a hospital ward
Huh.
if I thought that I would not correct people when I think they are wrong.
maybe you didn’t see me on this site when the death count was 0 and the case count
was 68..
telling people that the USA was not testing enough.
If I thought the truth was simply made up, why would I make any argument.
One thing I learned is that it was naive of me to believe that antibody testing would end the uncertainty.
On the whole a takeaway from mosh’s comments would be that we should ignore this study and wait for a well-designed randomized representative sample.
HIDE THE DECLINE!
I ran the numbers for WA state and Florida, and new cases peaked on 4/3/2020 for both states. The new Trump guidelines suggest that two weeks of declining infections are a prerequisite for easing stay-at-home orders. You are going to be seeing talking heads trying to hide the fact that new cases are declining.
50 out of 3300 were positive
based on the stats of their own test, 33% of these could be false positives.
Is this a John P.A. Ioannidis study?
Yup.
So major problems.
1. Not a random sample, you are likely to recruit people who
A) could not get a PCR test because they failed to meet the severe criteria required for that.
2. Included Children from the families and did not report out those stats
3. Test specificity and Sensitivity.
Do it again.
and report out all the raw data FFS
Ok.
This is a test done by recruitment over facebook.
Do you want to be tested?
well if you live in a county where you could not be PCR tested unless you had severe symptoms
then you would be motivated to sign up.
Hey, I was feeling ill in January, or I had a little cough in Feb, but I could not get tested.
I’m really curious, did I have COVID?
or
hey My girl friend tested positive and they never tracked me down to test me like they would
in Korea. I wonder maybe did I catch it? And gosh, maybe I gave it to my kid.
There’s free testing, lets go
And
Look at how many people faked data to show up for the test
101, more than tested positive
42 had invalid Id
59 had ID that didn’t match their survey
I will say this.
my prediction of less than 100 positive was correct.
It’s is good to see every reader practice skepticism and not try to fool themselves.
Feynman would be proud of all of you who read the paper BEFORE commenting.
and he would also be proud of all of you who bent over backwards to find issues with the study
That’s the skeptical spirit.
so if you did that, great.
if not, well no comment.
Bottom line: it is good news but not great news, and the science is not settled.
Plus they need to learn to post raw data and code.
The response to this study is as interesting as the content. In some ways, maybe more.
This makes maybe one time that I agree with Brother Mosher. You put ads on Facebook offering a free test to see if you have or have had Covid-19, who is most likely to sign up? People who think they may have had it, that is who. And they are allowed to bring a child, who typically would live in the same home?
This is not random sampling…
yep,
Telluride is probably better since they aim at testing everyone.
Still, the study is a good START cause it shows you how difficult it will be to get good data
IF
1. you are in an area where getting PCR tests was tough
2. you allow people to select in.
3. if the test sensitivity and specificity are low
4. If the spread is low..
Then you are going to have to get a very large sample.
So, the test will help others in designing a better test.
Folks should not object to doing a better job.
The authors themselves suggest as much
Food for thought:
This summer will come the adenovirus season. We now have the ability to identify, name, test and track every virus that comes along. Good thing, right? SO we can identify each “new” virus, yes? “New” means they have not been sequenced before, therefore each virus will be “new”. (Not new—ancient, coming cyclically like sine waves.) We were just never introduced properly.
Come October-November, and into next winter, we will have seasonal viruses come as follows (from CDC):
PIV-2,3
Rhinovirus(es)
RSV(s)
MPV
Then influenza(s)
Many of these will be “new”. With new names (identifiers). Tracking across all countries. New “medicines”. Lots of people selling new snake oil.
AND, all viruses are lethal (to the compromised). How will we react then?
In Karolinska Hospiltal, Sweden, 320 women that were about to deliver a child (all of them) were tested for COV-19 virus, no exeptions.
Of those, 23 tested positive.
All relatively young, resonably good health, female of course, no mention of symptomes.
Reported on swedish public television news, 10april.
Have they all be going to the same birth classes and/or sharing a midwife for education and exercises? Or did they simple got it from the hospital staff?
That’s a too small non-randomized sample.
No previous contacts, just all incoming soon-to- be mothers. Well some are probably already mothers.
So, quite random. Small sampe, yes.
1/. Government policy is being driven by death rates alone. This is interesting but wont affect policy.
2/. However what this does mean is that lock down is probably reducing the severity of the disease in the vast majority of the population and should make arriving at ‘herd immunity’ less painful than e.g. the WHO predict.
The prevalence of serious disease in densely populated areas does seem to indicate that case severity is critically dependent on viral load
questions you want to ask to stratify your test subjects
1. Do you take mass transit or exclusively use your car
2. do you attend church
3. Do you work or stay at home
4. Do you eat out
5. How often do you grocery shop
ect.
rather than gender and race why dont they collect variables that might differentiate on
social interaction.
Probly need a sample size at least 10x, with 50 positive cases they learn nothing about associated risk
factors
Well two things are emerging in the UK
1/. It’s raging through the densely packed cities and care homes and te medical profession and leaving the countryside essentially untouched.
2/. Where it rages BAME* people are massively more likely to die of it.
3/. Of course so to are the elderly etc. But that’s no surprise, as they tend to die of respiratory infections whenever they have other issues.
Point 1/. Essentially justifies lockdown. It almost shouts that more exposure equals far greater risk of serious illness and death.
Point 2/. Is extremely interesting. If it turns out for instance that massive doses of vitamin D make a difference…
Point 3/. is unimportant. It is to be expected.
“Black, Asian, Minority Ethnic”
In Germany, church attend is prohibited.
Who are the ones who get an immune over reaction (cykotine storm) and end up on intensive care with ventilators?
Elderly people and people with underlying conditions? YES
But also people who get the invitations for flu shots….
If it was a stronger virus mutatioon/string also babies and young children should be affected, since they have a weak immune system. Just like the normal flu pattern.
Since 2012 there is a lot of research on corona virus vaccins. A few years ago animals were tested with the 4 most promosing corona vaccins. The test seemed to go right, until the animals were months later exposed to a wild corona virus. Then it went terribly wrong. Massive immune over reactions with binding anti bodies, instead of neutralizing anti bodies.
The proposed medicine mix is Hydroxychloroquine, zink, and z-pack
Hydroxychloroquine is an immune over reaction modulator. Zink (anti viral infection), and z-pack (anti bacterial) are for cleaning up what the body immune system over reacts on.
https://aidsinfo.nih.gov/drugs/564/hydroxychloroquine/0/professional
Breaking news: COVID does not lead to ARDS, and we’re treating the wrong disease.
Confirmation of this from several sources so far:
A physician treating patients in NYC: https://www.hippocraticpost.com/covid-19-update/does-covid-19-really-cause-ards/
An Intensive Care Specialist (but not a physician): https://www.hippocraticpost.com/covid-19-update/has-covid-19-had-us-all-fooled/?utm_source=website&utm_medium=webpush&utm_campaign=notifications
The Chief of Pulmonary and Critical Care Medicine at a hospital: https://www.evms.edu/media/evms_public/departments/marketing__communications/EVMS_Critical_Care_COVID_19_Protocol__4_2_2020-revised.pdf
Better random sampling approach
I posted these comments on FB about a similar test from Massachusetts where the prevalence of SARS-CoV-2 is much greater than in the Bay Area:
My sister-in-law found a Massachusetts variant of this article. I replied, with some edits:
https://www.foxnews.com/science/third-blood-samples-massachusetts-study-coronavirus
Sigh. That Massachusetts article is okay, very promising, actually, but:
“Participants …provided a drop of blood to researchers, who were able to produce a result in ten minutes with a rapid test.”
This must be the serologic antibody test that’s been long awaited.
“He [the city manager] added: “Still, it’s kind of sobering that 30 percent of a random group of 200 people that are showing no symptoms are, in fact, infected.”
No, the purpose of the antibody test is to identify people who _had_ the disease. The are, in fact, recovered.
At any rate, 32% positive in one of the nations hotspots (the NH vs MA comparison is quite amazing).
That article links to a similar article from Santa Clara county in CA, https://www.foxnews.com/health/coronavirus-antibody-testing-finds-bay-area-infections-85-times-higher-reported-researchers
“Earlier this month, Stanford University-led researchers tested 3,330 adults and children in Santa Clara County, who were recruited using Facebook ads, for SARS-CoV-2 antibodies and found that the population prevalence of COVID-19 in Santa Clara ranged from 2.49 percent to 4.16 percent.” [Sigh. Covid-19 is the disease, so it found the prevalence of people who _recovered_ from Covid-19.]
I saw that story last night. It’s really important that so many cases are so minor. In CA’s case, they’re a long, long way to developing herd immunity. In Chelsea’s case, they’ve made a giant step there already, I imagine that NYC is even further along.
That suggests to me people in NYC will be astounded at how quickly Covid-19 fades from the scene, even without a cure that passes whatever muster people are demanding, or vaccine late this year or next.
The Massachusetts immunity research found 32% out of 200 participants testing positive while the Chelsea infection rate was only 2%. Immunity seems to be about 16 times the infection rate, which is the same ratio as in the Dutch research over 4000 people that I mentioned in the comment below.
So far 15-16 times the infection rate seems to be a more reasonable indication for the immunity rate.
https://wattsupwiththat.com/2020/04/17/covid-19-antibody-seroprevalence-in-santa-clara-county-california-coronavirus/#comment-2969259
How well do we trust the antibody test? Could it produce false positives, due to a person having antibodies to an earlier, different coronavirus infection?
Dave Burton: “How well do we trust the antibody test?”
WR: Not too much. We will have to wait for more results and for more reports about the tests themselves. For now the tests give only an indication. One of the questions is whether the test is specific enough for Covid-19.
Besides, the infection rate mentioned above also depends on the way of testing. In the Netherlands there is very restricted testing: not all cases are catched. In fact this makes the infection rate not comparable to the infection rate for another area where testing has been (more) complete.
I wonder just how reliable these results are – given the group tested were all volunteers.
Is it not possible that people who had mild or severe flu symptoms and suspected they had nCOV, are more likely to volunteer to be tested?
If so, it wouldn’t take much over-representation to skew the results.
Testing random groups of people would be more representative.
I was a scientist in animal and human medical trials in large and medium sized Pharma. I am retired, but still do evaluations for State and Federal grants to universities.
All of these tests we are talking about here don’t seem to account for Placebo Effect. I remember studying about how to minimize this powerful effect. Placebo Effect can account for 30-40% of results.
Do I trust the doctor? How much? This is a powerful actor in these studies.
Is there confirmation bias? The mind is a powerful thing.
These are why we need double blinding in order to find out, with confidence, that we are accurately seeing what nature is telling us.
Also, we are looking for a rare event (death end point). When looking for a confidence result of, say 95% confidence (P<0.05), for a rare event, I remember being shocked that we would require about 200 people in each group, both treated and non-treated, where both the subject and the studier are removed in a randomized fashion.
We had a textbook that we would use called, "Statistics of Rare Events". Surprisingly large numbers of replication had to be used. As the rare event incidence is lower and lower, the number of replications needed goes up geometrically.
It is confusing for people trying to make sense of this stuff. Common sense has its limitations, because nature most often is counter-intuitive.
Enjoy life and forget about mocktons and jo novas who live in horrible countries like Britain and Australia with no personal freedoms dictartorships police states and no nothing about cold viruses or knows nothing about climate or metereology Viva America https://onlineradiobox.com/br/bossanova/?cs=br.bossanova&played=1&lang=en